Build the LBNL-4944E data model. This function takes a data grid containing the load, temperature and occupancy historical data, and returns a data model similar to the one in LBNL-4944E. The most notable difference is that occupancy is modeled using a 0 or 1 instead of creating a separate model for both modes.
state parameter is a dictionary which may contain the following keys for configuring LBNL:
intervals: The number of temperature intervals to use. (default: 6)
minTemp: The minimum temperature to use for computing temperature
intervals. By default, we find the min temperature of the temp column.
maxTemp: The maximum temperature to use for computing temperature intervals. By default we find the max temperature of the temp column.
Perform LBNL-4944E forecasting using a model trained by lbnlTrain for the given dates. Returns a grid containing the recent power, forecasted power, and occupancy. The
opts parameter currently supports the following options:
backcast: set this marker tag to do "backcasting"
Get a trained model using the methodology outlined in LBNL-4944E.
site: The site to train the model against. Must have a site meter
with a power sensor point.
dates: Use historical data from this date range for training the model.
The model metadata will include the computed